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Fully-sensitive seed finding in sequence graphs using a hybrid index

机译:使用杂种索引在序列图中完全敏感的种子发现

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摘要

MotivationSequence graphs are versatile data structures that are, for instance, able to represent the genetic variation found in a population and to facilitate genome assembly. Read mapping to sequence graphs constitutes an important step for many applications and is usually done by first finding exact seed matches, which are then extended by alignment. Existing methods for finding seed hits prune the graph in complex regions, leading to a loss of information especially in highly polymorphic regions of the genome. While such complex graph structures can indeed lead to a combinatorial explosion of possible alleles, the query set of reads from a diploid individual realizes only two alleles per locus—a property that is not exploited by extant methods.
机译:MotivationSequence图是通用的数据结构,例如,它能够代表种群中发现的遗传变异并促进基因组组装。读取到序列图的映射是许多应用程序的重要步骤,通常通过首先找到精确的种子匹配来完成,然后通过比对进行扩展。现有的寻找种子命中的方法会在复杂区域修剪图,导致信息丢失,尤其是在基因组的高度多态性区域。虽然这种复杂的图结构确实可以导致可能的等位基因组合爆炸,但从二倍体个体读取的查询集每个位点只能实现两个等位基因-现有方法无法利用此特性。

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